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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

r-Process nucleosynthesis from three-dimensional jet-driven core-collapse supernovae with magnetic misalignments

We investigate r-process nucleosynthesis in three-dimensional general relativistic magnetohydrodynamic simulations of jet-driven supernovae resulting from rapidly rotating, strongly magnetized core-collapse. We explore the effect of misaligning the pre-collapse magnetic field with respect to the rotation axis by performing four simulations: one aligned model and models with 15°, 30°, and 45° misalignments. The simulations we present employ a microphysical finite-temperature equation of state and a leakage scheme that captures the overall energetics and lepton number exchange due to post-bounce neutrino emission and absorption. We track the thermodynamic properties of the ejected material with Lagrangian tracer particles and analyse its composition with the nuclear reaction network SKYNET. By using different neutrino luminosities in post-processing the tracer data with SKYNET, we constrain the impact of uncertainties in neutrino luminosities. We find that, for the aligned model considered here, the use of an approximate leakage scheme results in neutrino luminosity uncertainties corresponding to a factor of 100–1000 uncertainty in the abundance of third peak r-process elements. Our results show that for misalignments of 30° or less, r-process elements are robustly produced as long as neutrino luminosities are reasonably low (≲ 5 × 10 52 erg s -1 ). For a more extreme misalignment of 45°, we find the production of r-process elements beyond the second peak significantly reduced. We conclude that robust r-process nucleosynthesis in magnetorotational supernovae requires a progenitor stellar core with a large poloidal magnetic field component that is at least moderately (within ~30°) aligned with the rotation axis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

NuGrid stellar data set – III. Updated low-mass AGB models and s-process nucleosynthesis with metallicities Z= 0.01, Z = 0.02, and Z = 0.03

ABSTRACT The production of the neutron-capture isotopes beyond iron that we observe today in the Solar system is the result of the combined contribution of the r-process, the s-process, and possibly the i-process. Low-mass asymptotic giant branch (AGB) (1.5 < M/M⊙ < 3) and massive (M > 10 M⊙) stars have been identified as the main site of the s-process. In this work we consider the evolution and nucleosynthesis of low-mass AGB stars. We provide an update of the NuGrid Set models, adopting the same general physics assumptions but using an updated convective-boundary-mixing model accounting for the contribution from internal gravity waves. The combined data set includes the initial masses MZAMS/M⊙ = 2, 3 for Z = 0.03, 0.02, 0.01. These new models are computed with the mesa stellar code and the evolution is followed up to the end of the AGB phase. The nucleosynthesis was calculated for all isotopes in post-processing with the NuGrid mppnp code. The convective-boundary-mixing model leads to the formation of a 13C-pocket three times wider compared to the one obtained in the previous set of models, bringing the simulation results now in closer agreement with observations. Using these new models, we discuss the potential impact of other processes inducing mixing, like rotation, adopting parametric models compatible with theory and observations. Complete yield data tables, derived data products, and online analytic data access are provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Parametrized process characterization with reduced resource requirements

Quantum process tomography (QPT) is a powerful tool to characterize quantum operations, but it requires considerable resources, making it impractical for more than two-qubit systems. This study proposes an alternative approach that requires significantly fewer resources for unitary process characterization with a built-in method for state preparation and measurement error mitigation. By measuring the quantum process as rotated through the X and Y axes on the Bloch sphere, we can acquire enough information to reconstruct the quantum process matrix χ and measure its fidelity. We test the algorithm's performance against standard QPT using simulated and physical experiments on several IBM quantum processors and compare the resulting process matrices. We demonstrate with numerical experiments that the method can improve gate fidelity via a noise reduction in the imaginary part of the process matrix, along with a stark decrease in the number of experiments needed to perform the characterization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Shadow process tomography of quantum channels

Quantum process tomography is a critical capability for building quantum computers, enabling quantum networks, and understanding quantum sensors. Like quantum state tomography, the process tomography of an arbitrary quantum channel requires a number of measurements that scales exponentially in the number of quantum bits affected. However, the recent field of shadow tomography, applied to quantum states, has demonstrated the ability to extract key information about a state with only polynomially many measurements. In this work, we apply the concepts of shadow state tomography to the challenge of characterizing quantum processes. Furthermore, we make use of the Choi isomorphism to directly apply rigorous bounds from shadow state tomography to shadow process tomography, and we find additional bounds on the number of measurements that are unique to process tomography. Our results, which include algorithms for implementing shadow process tomography, enable new techniques including evaluation of channel concatenation and the application of channels to shadows of quantum states. This provides a dramatic improvement for understanding large-scale quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Practical and reliable error bars for quantum process tomography

Current techniques in quantum process tomography typically return a single point estimate of an unknown process based on a finite albeit large amount of measurement data. Due to statistical fluctuations, however, other processes close to the point estimate can also produce the observed data with near certainty. Unless appropriate error bars can be constructed, the point estimate does not carry any sound operational interpretation. Here, we provide a solution to this problem by constructing a confidence region estimator for quantum processes. Our method enables reliable estimation of essentially any figure of merit for quantum processes on few qubits, including the diamond distance to a specific noise model, the entanglement fidelity, and the worst-case entanglement fidelity, by identifying error regions which contain the true state with high probability. We also provide a software package, QPtomographer, implementing our estimator for the diamond norm and the worst-case entanglement fidelity. We illustrate its usage and performance with several simulated examples. Furthermore, our tools can be used to reliably certify the performance of, e.g., error correction codes, implementations of unitary gates, or more generally any noise process affecting a quantum system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Direct cross-section measurement of the weak r -process Sr 88 ( α , n ) Zr 91 reaction in ν -driven winds of core-collapse supernovae

About half of the heavy elements beyond iron are known to be produced by the rapid neutron capture process, known as the r process. However, the astrophysical site producing the r process is still uncertain. Chemical abundances observed in several cosmic sites indicate that different mechanisms should be at play. For instance, the abundances around silver measured in a subset of metal-poor stars indicate the presence of a weak r process. This process may be active in neutrino-driven winds of core collapse supernovae where (α,n) reactions dominate the synthesis of Ζ ≈ 40 elements in the expelled materials. Scarcely measured, the rates of (α,n) reactions are determined from statistical Hauser-Feshbach calculations with α-optical-model potentials, which are still poorly constrained. Further, the uncertainties of the (α,n) reaction rates therefore make a significant contribution to the uncertainties of the abundances determined from stellar modeling. In this work, the 88 Sr (α,n)⁢ 91 Zr reaction which impacts the weak r-process abundances has been probed at astrophysics energy for the first time; directly measuring the total cross sections at astrophysical energies of 8.37–13.09 MeV in the center of mass (3.8–7.5 GK). Two measurements were performed at ATLAS with the electrically segmented ionization chamber MUSIC, in inverse kinematics, while following the active target technique. The cross sections of this α-induced reaction on 88 Sr, located at the shell closure N = 50, have been found to be lower than expected, by a factor of 3, despite recent statistical calculations validated by measurements on neighboring nuclei. This result encourages more experimental investigations of (α,n) reactions, at Ν = 50 and towards the neutron-rich side, to further test the predictive power and reliability of such calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Effect of process route on powder three-dimensional-printing of metal powders

The purpose of this study is to investigate the effect of two unique processing routes (solvent jetting (SJ) and binder jetting (BJ)), on the green density of printed stainless steel 316L (SS316L) and Nickel (Ni) powders. In the SJ processing route, a solvent is jetted unto the powder/binder mixture to selectively activate the binder, layer by layer. In the BJ processing route, a solution of the binder mixture is jetted onto the powder bed to selectively bind powder particles. The effects of printing parameters such as layer height, roller speed, shaker speed and nozzle temperature on the green density of printed components are investigated and compared for both processing routes. Results show that layer height and nozzle temperature affect the relative density of the printed compact for both processing routes. Slightly higher relative densities were achieved via the SJ route, with the overall highest relative density being 42.7% at 100 µ m layer height and 70% nozzle temperature for the SS316L components and 43.7% at 150 µ m layer height and 90% nozzle temperature for the Ni components, respectively. Results also show an increase in the final sintered relative density with an increase in green (printed) relative density of the solvent jetted SS316L components, with the highest relative density being 87.2%. The paper studies the influence of printing parameters on the green density of printed SS316L and Ni samples in an unprecedented effort to provide a comparative understanding of the process-property relationships in BJ and SJ of SS316L and Ni components to the additive manufacturing research community.

Engineering↗
DOE OSTI2023

Process-dependent anisotropic thermal conductivity of laser powder bed fusion AlSi10Mg: impact of microstructure and aluminum-silicon interfaces

Purpose AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity. Design/methodology/approach The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity. Findings The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm 3 and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm 3 . The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains. Practical implications The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications. Originality/value To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

Engineering↗
DOE OSTI2021

Effects of Wire Diameter and Filament Size on the Processing Window of Bi-2212 Round Wire

High engineering critical current density (J E of 1300 A/mm 2 at 4.2 K and 15 T) in Bi-2212 round wire has been achieved through a partial melt, overpressure heat treatment process. J E varies strongly with processing conditions, particularly the maximum heat treatment temperature (T max ). Increasing T max results in longer time in the melt (defined as the time between when Bi-2212 melts on heating and when Bi-2212 begins to form on cooling), more bridging between the filaments, lower J E , and higher ac losses. A wide processing window with a large range of T max that has a nearly constant J E is desired for processing large coils with large thermal mass and significant thermal time constants that may make precise control over the desired temperature – time profiles uncertain. Accordingly, we wanted to explore broadening the T max window by controlling the Bi-2212 powder melting or wire architecture design. In this work, we report on studies of the performance variation with T max for two production wires with a filling factor of about 20% and 85 × 18 filaments where filament size was varied by changing the wire diameter, a process which also shortens the distance between filaments. We found that wires with smaller filament diameter (9 to 11 μm) showed a peak J E at the low end of T max and also a J E that was more sensitive to T max . A J E – T max plot showed a plateau J E (4.2 K, 5 T) of ~1100 A/mm 2 between T max of 886 and 894 °C for 1.0 and 1.2 mm wires, where J E is less sensitive to the wire diameter and T max . This J E plateau range is a preferred processing window for achieving high J E in coils.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Analytical Study and Experimental Verification of Shear-Thinning Ink Flow in Direct Ink Writing Process

Abstract Direct ink writing (DIW) process is a facile additive manufacturing technology to fabricate three-dimensional (3D) objects with various materials. Its versatility has attracted considerable interest in academia and industry in recent years. As such, upsurging endeavors are invested in advancing the ink flow behaviors in order to optimize the process resolution and the printing quality. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and its underlying theories. Here, we present a comprehensive analytical study of non-Newtonian ink flow behavior during the DIW process. Different syringe-nozzle geometries are modeled for the comparative case studies. By using the computational fluid dynamics (CFD) simulation method, we reveal the shear-thinning property during the ink extrusion process. Besides, we study the viscosity, shear stress, and velocity fields, and analyze the advantages and drawbacks of each syringe-nozzle model. On the basis of these investigations and analyses, we propose an improved syringe-nozzle geometry for stable extrusion and high printing quality. A set of DIW printing experiments and rheological characterizations are carried out to verify the simulation studies. The results developed in this work offer an in-depth understanding of the ink flow behavior in the DIW process, providing valuable guidelines for optimizing the physical DIW configuration toward high-resolution printing and, consequently, improving the performance of DIW-printed objects.

Engineering↗
DOE OSTI2026

Identifying Bounds of Inorganic Content in Solventless Processing of Hybrid Solid Electrolytes

Solid-state lithium batteries require safe, robust electrolytes to enable higher energy densities and improved safety over conventional cells. Hybrid polymer–ceramic electrolytes are a promising solution, combining the processability of polymers with the high ionic conductivity and mechanical strength of inorganic fillers. In this work, we demonstrate a solventless, UV-curing method to produce hybrid solid electrolytes using a poly(ethylene glycol) dimethyl ether (PEGDME)-based photocurable matrix incorporating Li 1.5 Al 0.5 Ge 1.5 (PO 4 ) 3 (LAGP) or Li 7 La 3 Zr 2 O 12 (LLZO) ceramic electrolyte. Inorganic filler loadings up to ∼55 wt.% could be successfully incorporated via this process which was the highest inorganic content at which the slurry remains processable and cured into a uniform film. The resulting UV-cured composite electrolytes remain flexible and exhibit room-temperature ionic conductivities on the order of 10 −4 S·cm −1 , along with notably improved lithium-ion transference numbers compared to conventional polymer electrolytes. Similar performance and processing limits were observed for both LAGP and LLZO, indicating that ceramic filler chemistry does not significantly affect the UV-curing process or the electrolyte's ion transport properties in this regime. Eliminating solvents from fabrication not only simplifies processing and mitigates environmental concerns but also enables higher solid contents that enhance mechanical strength and help suppress lithium dendrite formation. In conclusion, this scalable approach thus paves the way for manufacturing robust composite solid electrolytes for next-generation solid-state batteries (SSBs).

Batteries↗
DOE OSTI2018

Effect of Barothermal Processing on the Solid-State Formation of the Structure and Properties of 16 at % Si–Al Hypereutectic Alloy

We describe barothermal processing (hot isostatic pressing) of a 16 at % Si–Al binary alloy for 3 h at a temperature of 560°C and pressure of 100 MPa for 3 h, in combination with measurements of heat effects during cooling. The results demonstrate that this processing leads to the fragmentation of the silicon structural constituent and ensures a high degree of homogenization of the as-prepared alloy. Heat treatment of the 16 at % Si–Al alloy at 560°C and a pressure of 100 MPa leads to a thermodynamically driven enhanced silicon dissolution, up to ~10 at %, in the aluminum matrix, resulting in the formation of a supersaturated solid solution, which subsequently decomposes during cooling. We analyze the complete porosity elimination process, which makes it possible to obtain a material with 100% relative density. According to differential barothermal analysis, microstructural analysis, and scanning and transmission electron microscopy data, barothermal processing of the 16 at % Si–Al alloy produces a bimodal size distribution of the silicon phase constituent: microparticles 3.6 μm in average size and nanoparticles down to ~1 nm in diameter. The Al matrix has been shown to contain a high density of edge dislocations. Barothermal processing reduces the thermal expansion coefficient and microhardness of the hypereutectic alloy. We conclude that solid-state barothermal processing is an effective tool for completely eliminating microporosity from the 16 at % Si–Al alloy, reaching a high degree of homogenization, and controlling the microstructure of the alloy, in particular by producing high dislocation density in the aluminum matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stochastic representation and conditioning of process-based geological model by deep generative and recognition networks

Accurate and realistic geological modeling is the core of oil and gas development and production. In recent years, process-based methods are developed to produce highly realistic geological models by simulating the physical processes that reproduce the sedimentary events and develop the geometry. However, the complex dynamic processes are extremely expensive to simulate, making process-based models difficult to be conditioned to field data. In this work, we propose a comprehensive generative adversarial network framework as a machine-learning-assisted approach for mimicking the outputs of process-based geological models with fast generation. The main objective of our work is to obtain a continuous parametrization of the highly realistic process-based geological models which enables us to calibrate the models and condition the models to data. Numerical results are presented to illustrate the capability of our proposed methodology.

58 GEOSCIENCES↗
DOE OSTI2024

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗
DOE OSTI2025

Modeling a High-Temperature Electrochemically Driven Water-Gas-Shift Process Using a Mixed-Conducting Membrane without External Electrical Power

This paper develops a model to predict and interpret the performance of an elevated-temperature, electrochemical, membrane-assisted, water-gas-shift process. The process uses separated feed streams of H 2 O and CO to produce separated streams of H 2 and CO 2 , without an external electrical power source. The dense ceramic membrane is mixed ionic-electronic-conducting (MIEC) gadolinium-doped ceria (GDC) and the porous composite electrodes are Ni-YSZ. At elevated temperature, GDC conducts both oxygen ions and small polarons. The present process uses chemical potential to drive the process. Electrochemical oxidation of CO proceeds within the composite anode and H 2 O reduction proceeds within the composite cathode. At high temperature (e.g., T > 700 °C), GDC has significant electronic leakage in the form of a reduced-cerium small polaron, which supports the charge-transfer reactions. In a typical electrolyzer or fuel cell, this leakage is significantly problematic. However, the present process depends on the leakage current to complete the electrochemical circuit. Model development and validation is based on measured material properties and reactor performance. Potential applications include using CO-rich blast-furnace off gases in steel processing, producing separated streams of H 2 and CO 2 .

Zhu, Huayang↗
DOE OSTI2022

Idaho National Laboratory Data Acquisition And Processing System

The INLDAS data acquisition and processing system is designed to develop prototype measurements and real-time processing techniques. The INLDAS hardware and firmware currently consists of National Instruments • NI-DAQmx 14.1 • cDAQ-9184 • 9205 • 9211 INLDAS can perform of standard data acquisition functions as well as novel functions and real-time processing algorithms. There are 3 acquisition modes to choose from: • Continuous mode runs when the user hits start, processing data and logging it to file • SWTrigger mode waits for one or more predefined triggers before acquiring data. It will buffer data as well, so it can record data that happened shortly before the trigger • Wakeup mode waits on predefined timers. When a time goes off, it acquires a preset amount of data There are also 3 Data Processing Modes • Normal mode does no processing besides the rolling average • FFT Mode Performs an FFT on incoming data every time the time window has elapsed • STFFT mode

Smith, JamesA↗
DOE OSTI2023

Processing Temperature Effect on Failure Behavior of Unidirectional Thermoplastic Polymer-fiber-reinforced Polymers (PFRPs)

This study aimed to examine the influence of processing temperature on the mechanical and morphological characteristics of unidirectional (UD) thermoplastic polymer-fiber-reinforced polymers (PFRPs), utilizing UHMWPE-polymer-fiber-reinforced HDPE composites as an example. To achieve this objective, UD thermoplastic PFRPs were produced through filament winding and hot pressing techniques, employing five distinct processing temperatures within the range spanning from the melting onset temperature of the polymer matrix to the melting peak temperature of the reinforcing polymer fiber. By conducting the uni-axial tensile tests on the UD UHMWPE-polymer-fiber-reinforced HDPE composites fabricated at different processing temperatures, it was shown that the optimal longitudinal tensile properties of the composites, comparable with glass-fiber-reinforced thermoset or thermoplastic polymers (GFRPs or GFRTPs) can be achieved when the processing temperature does not significantly exceeds the melting onset temperature of the reinforcing polymer fiber. However, when the processing temperature exceeds this threshold, the mechanical properties of the composites are significantly reduced, as evidenced by the transition in the failure morphology from the presence of significant splitting cracks to the occurrence of plastic necking due to the complete melting of the reinforcing polymer fibers in a composite. Particularly, the ductile behavior of the optimal thermoplastic PFRPs investigated in this study is superior than that of carbon-fiber-reinforced thermoset or thermoplastic polymers (CFRPs or CFRTPs) and even GFRPs and GFRTPs. This study not only provides valuable insights into the proper fabrication of high-performance thermoplastic PFRPs but also offers useful experimental data that can aid in the validation and development of computational models, particularly those related to processing modeling.

Qiao, Yao↗